AI has gone a long way from science fiction and theories to implementations in many areas of everyday life. Such an illustrious evolution has become possible thanks to the efforts of both scientists and software engineers. However, the development of Artificial Intelligence and Machine Learning does not stop. AI technologies are gradually making their way to new areas of interest and finding new implementations in already established fields. Let’s see how AI and ML interact with their “hearth and home” - the field of software engineering.
Definition of AI and Its Various Applications in Software Development
Artificial Intelligence is one of the oldest concepts, originating from ancient times and myths. However, it was not until the 20th century when old ideas and crude prototypes got practical realization. Many prominent mathematicians, logicians, and computer scientists joined their efforts to define the concepts of “reasoning” and “learning” in the context of computers. The works of Alan Turing, Arthur Samuel, Tom M. Mitchell, and many others created the base for the progress of AI and ML technologies and computer algorithms and programming languages in general.
The generally recognized features that define AI are the ability to solve complex problems and the ability to generate information based on the source parameters. This way, researchers focus on the similarities between “human” thinking and “machine” thinking. Artificial Intelligence also should have the ability to learn, with human supervision or without it.
Thanks to the rapid progress of AI and ML technologies, they have been successfully integrated into many key areas of modern life. For example, the bond between AI and software development turned into two-way beneficial cooperation. This means that Artificial Intelligence has two major layers of interaction with software engineering.
- It is an immensely useful tool that helps developers with numerous tasks. An AI paired with great computational power and data storage capabilities easily outperforms human abilities.
- It is an object of software developers’ labor. Software engineers are often tasked to create an AI for specific purposes or to integrate an existing AI into a solution that is being developed.
Let’s take a look at both of these areas of interaction.
The Applications of Artificial Intelligence in Software Engineering
Software developers have mastered the art of training and customizing AI for various purposes. In general, state-of-the-art AI has unparalleled abilities for data mining, analysis, and classification. Those abilities also make Artificial Intelligence a great assistant capable of understanding requests and finding solutions. Here are a few examples of using AI technologies in software development:
Code Generation
Modern AI can write code based on given parameters. The results, on average, are quite satisfactory but not enough to replace a skilled programmer. However, specialized AIs and learning models are getting progressively better. It is just a matter of time until they become on par with junior-level specialists. This pace of progress should be a clear signal for software engineers to keep improving their skills.
The machine-written code still requires comprehensive checking from experienced specialists, especially regarding its security. In the near future, this tendency may change the role of software developers. It is possible that AI will perform the “writing”, and developers will switch to “editing” the code. This way, Artificial Intelligence will do the bulk of hard and mundane work, and software engineers will oversee this process.
Requirements Gathering
Developers often use Artificial Intelligence to compile a set of requirements for a future software product. It optimizes workflow and reduces the flow of documents associated with this task. AI proves to be extremely useful in demanding projects with complex requirements.
For example, Watson AI, developed by IBM, is especially useful for requirements management. In addition, it effectively assists in other stages of the software development life cycle. The use of AI eliminates or at least reduces the need for going through lots of paper and digital documentation manually.
Planning, Estimating, and Designing
Based on the gathered requirements, AI can take over the rest of the software development process. It is more efficient in tasks that require calculations, such as estimating costs and scheduling deadlines. It also can determine the development team setup and the number of required specialists to meet the deadlines within the set budget.
Of course, this process is closely supervised by managers. So, the role of AI here is to make rough drafts rather than final plans. It can also make suggestions regarding workflow optimization. However, humans still have the final word regarding AI advice.
Quality Control and Feedback Management
Artificial Intelligence can also assist developers by running error scans and looking for vulnerabilities in code. Software engineers can train AI using the existing guidelines and checklists for ensuring software security. Then, any particular development company can customize and enhance obtained machine learning models individually. The specialists can turn those models into intellectual property by training them on every software product created by that company.
AI is also invaluable for gathering feedback from users and testers in a convenient automated form. It can analyze reports and divide them into categories depending on the nature of feedback (positive/negative), the severity of a reported error (critical/major/minor), and other parameters. The resulting structured data will be much more useful for the purposes of QA than the bulk of assorted reports.
Areas and Industries That Use AI-powered Solutions
As was described above with reference to software development, specialists use AI for two general purposes. One purpose involves Artificial Intelligence performing tasks automatically with or without human supervision. The other purpose is to improve the productivity of human workers by assisting them and enhancing their abilities. Below are a few illustrative implementations of AI in different areas outside software development.
- Data mining. One of the main purposes of AI nowadays is to gather enormous amounts of raw data on the Internet. It is the task of web crawlers that are used in search engines, including Google, Bing, Baidu, and others. However, those and other interested companies, such as Meta, Twitter, Amazon, etc., are also collecting information about their users. Every user’s activity on the Internet is usually tracked by several companies simultaneously. The resulting data flow would be impossible without the help of Artificial Intelligence.
- Data analysis, classification, and statistics. AI is also responsible for analyzing user data mainly for the benefit of Internet corporations. It defines behavior patterns, habits, and preferences for every user account. The resulting data is used for targeted advertising and other types of personalized content. The latter is especially true in the case of social networks and streaming services.
- AI assistants in smart devices. Artificial Intelligence is often integrated into gadgets to make them more convenient and resourceful. The most common types are, of course, smartphones, tablets, and speakers. This is because they have the necessary hardware to listen to users and respond, preferably using AI-generated voice.
- Autonomous driving. Artificial Intelligence enables AI-assisted driving in the form of an autopilot that can be toggled on and off. It also allows fully autonomous driverless operation of vehicles in certain environments.
- Gaming. One of the earliest showcases of AI was in the form of chess computers. Specialized versions of AI are also used for such table games as go, backgammon, and poker. Artificial Intelligence is widely used in the video game industry, both in single-player and multiplayer games. It controls enemies, NPCs, and bots in order to react to players’ actions.
- Writing and maintaining a dialogue. ChatGPT and its analogs are the hottest topics in all the tech news these days. They can hold written conversations with users and are often tasked to write letters, articles, and even scientific papers.
- Creating visual art. The combination of AI and ML gave several amazing tools for visual artists and designers. Midjourney, DALL-E 2, and Neural filters in Adobe Photoshop are the most popular examples of such instruments.
The Benefits of Artificial Intelligence for Developers
From the description above, it is clear that Artificial Intelligence and Machine Learning offer many advantages. Most of them can be effectively applied to benefit software development. Here are a few ways how AI improves the work of software engineers:
- Precise planning
- Predictable workflow
- Informed decision-making
- Accurate estimates
- Better security and QA
- Reduced workload
Overall, the main benefits of AI and ML in software development come down to higher efficiency and lower costs. Artificial Intelligence helps to automate many time-consuming processes. This allows managers to switch specialists from boring routine tasks to more creative and responsible assignments.
Additionally, these benefits offered by AI allow engineers to tackle more complex tasks that would otherwise be unfeasible or extremely costly. Ultimately, Artificial Intelligence enables the creation of more enhanced versions of itself. And those better versions will be able to solve even more difficult tasks, thus increasing the benefits.
Challenges of Using AI in Software Development
- Higher demands for specialists’ skills. AI is a sophisticated tool capable of performing many tasks. However, to fully utilize its potential, it must be operated by a specialist with sufficient skills and experience. The main requirement is the ability to formulate all the input parameters with maximum precision. In other words, users must say exactly what they want to achieve and describe it in full detail.
- Advanced tools require large computational power, storage space, and energy supply. A software development company that heavily relies on AI technologies has to invest in top-tier hardware. Better equipment usually means that AI would perform its tasks faster. In its turn, this would speed up the work of the development team and reduce the time to release the final product.
- Extra licensing costs. Professional tools are not cheap, especially in the software development business. Most state-of-the-art AI and ML solutions involve a hefty price for their commercial use. However, the costs are reasonable and more than justified. AI-enhanced tools quickly pay for themselves, especially when they are used by skilled software engineers.
The Future of AI in Software Development
It is safe to admit that AI technologies are the present and future of mankind. They have been successfully integrated into both personal and professional aspects of our lives. This means more work for software developers who create and implement custom AIs.
The combination of Artificial Intelligence, software engineering and Machine Learning is growing more powerful as the technologies improve every day. Moreover, software developers can now use specialized AIs to create other AIs. The circle has come to a close. But it also created the foundation of the constant evolution of Artificial Intelligence, allowing engineers to create better versions of AI with improved abilities.
Though the use of AI simplifies the work of software developers, it also demands high levels of skill and knowledge. This is especially true when engineers need to integrate Artificial Intelligence into custom software solutions. Our team in Intellectsoft has enough know-how and experience to handle complex and challenging AI-related cases. We offer a range of AI development services for various industries. Contact us to bring the advantages of Artificial Intelligence to your software.
